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A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

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A Structure Theorem for Level Sets of Multiplicative Functions and Applications

Florian Karl Richter

Given a level set E of an arbitrary multiplicative function f, we establish, by building on the fundamental work of Frantzikinakis and Host [14, 15], a structure theorem that gives a decomposition of

1_{E}

into an almost periodic and a pseudo-random part ...

2020

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

Graph Chatbot

Chattez avec Graph Search

SD-Pose: Semantic Decomposition for Cross-Domain 6D Object Pose Estimation

A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks

A Structure Theorem for Level Sets of Multiplicative Functions and Applications

Interfacial Effect between Aluminum-Based Complex Hydrides and Nickel-Containing Porous Carbon Sheets

Optimal Design of Heat-Integrated Water Allocation Networks

Lagrangian relaxation for the demand-based benefit maximization problem

A Lagrangian relaxation technique for the demand-based benefit maximization problem

Integrating advanced discrete choice models in mixed integer linear optimization

SD-Pose: Semantic Decomposition for Cross-Domain 6D Object Pose Estimation

A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks

A Structure Theorem for Level Sets of Multiplicative Functions and Applications

Interfacial Effect between Aluminum-Based Complex Hydrides and Nickel-Containing Porous Carbon Sheets

Optimal Design of Heat-Integrated Water Allocation Networks

A Lagrangian relaxation technique for the demand-based benefit maximization problem

Integrating advanced discrete choice models in mixed integer linear optimization

Lagrangian relaxation for the demand-based benefit maximization problem